{"title":"一种基于人工逻辑蜘蛛网的MPLS网络重路由机制","authors":"Xinyu Yang, Yi Shi","doi":"10.1142/S1469026805001520","DOIUrl":null,"url":null,"abstract":"Multiprotocol label switching (MPLS) is a hybrid solution that combines the advantages of easy forwarding with the ability of guaranteeing quality-of-service (QoS). To deliver reliable service, MPLS requires traffic protection and recovery. Rerouting is one such recovery mechanism. In this paper, we propose a novel rerouting model called DDRAAS that is inspired by the spider and its web in nature. We try to establish an artificial logical spider web in the MPLS network to reorganise it into a structure that is more regular and simple. Based on this, we give the definition of the reroute area. Artificial spiders are then used to explore recovery paths dynamically in the reroute area. DDRAAS can be used to calculate the recovery paths in advance in order to protect the work path, while the improved DDRAAS can be a fast rerouting algorithm to calculate and establish recovery paths when faults occur. We have simulated our mechanism using the MPLS network simulator (MNS) and the performance metrics were compared to those of other proposals. The simulation results show that our mechanism is better in reducing packet loss, disorder and has faster rerouting speed. These improvements help to minimise the effects of link failure and/or congestion.","PeriodicalId":45994,"journal":{"name":"International Journal of Computational Intelligence and Applications","volume":"05 1","pages":"119-139"},"PeriodicalIF":0.8000,"publicationDate":"2005-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1142/S1469026805001520","citationCount":"0","resultStr":"{\"title\":\"A NOVEL MECHANISM BASED ON ARTIFICIAL LOGICAL SPIDER WEB FOR REROUTING IN MPLS NETWORKS\",\"authors\":\"Xinyu Yang, Yi Shi\",\"doi\":\"10.1142/S1469026805001520\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Multiprotocol label switching (MPLS) is a hybrid solution that combines the advantages of easy forwarding with the ability of guaranteeing quality-of-service (QoS). To deliver reliable service, MPLS requires traffic protection and recovery. Rerouting is one such recovery mechanism. In this paper, we propose a novel rerouting model called DDRAAS that is inspired by the spider and its web in nature. We try to establish an artificial logical spider web in the MPLS network to reorganise it into a structure that is more regular and simple. Based on this, we give the definition of the reroute area. Artificial spiders are then used to explore recovery paths dynamically in the reroute area. DDRAAS can be used to calculate the recovery paths in advance in order to protect the work path, while the improved DDRAAS can be a fast rerouting algorithm to calculate and establish recovery paths when faults occur. We have simulated our mechanism using the MPLS network simulator (MNS) and the performance metrics were compared to those of other proposals. The simulation results show that our mechanism is better in reducing packet loss, disorder and has faster rerouting speed. These improvements help to minimise the effects of link failure and/or congestion.\",\"PeriodicalId\":45994,\"journal\":{\"name\":\"International Journal of Computational Intelligence and Applications\",\"volume\":\"05 1\",\"pages\":\"119-139\"},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2005-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1142/S1469026805001520\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Computational Intelligence and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1142/S1469026805001520\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Computational Intelligence and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1142/S1469026805001520","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
A NOVEL MECHANISM BASED ON ARTIFICIAL LOGICAL SPIDER WEB FOR REROUTING IN MPLS NETWORKS
Multiprotocol label switching (MPLS) is a hybrid solution that combines the advantages of easy forwarding with the ability of guaranteeing quality-of-service (QoS). To deliver reliable service, MPLS requires traffic protection and recovery. Rerouting is one such recovery mechanism. In this paper, we propose a novel rerouting model called DDRAAS that is inspired by the spider and its web in nature. We try to establish an artificial logical spider web in the MPLS network to reorganise it into a structure that is more regular and simple. Based on this, we give the definition of the reroute area. Artificial spiders are then used to explore recovery paths dynamically in the reroute area. DDRAAS can be used to calculate the recovery paths in advance in order to protect the work path, while the improved DDRAAS can be a fast rerouting algorithm to calculate and establish recovery paths when faults occur. We have simulated our mechanism using the MPLS network simulator (MNS) and the performance metrics were compared to those of other proposals. The simulation results show that our mechanism is better in reducing packet loss, disorder and has faster rerouting speed. These improvements help to minimise the effects of link failure and/or congestion.
期刊介绍:
The International Journal of Computational Intelligence and Applications, IJCIA, is a refereed journal dedicated to the theory and applications of computational intelligence (artificial neural networks, fuzzy systems, evolutionary computation and hybrid systems). The main goal of this journal is to provide the scientific community and industry with a vehicle whereby ideas using two or more conventional and computational intelligence based techniques could be discussed. The IJCIA welcomes original works in areas such as neural networks, fuzzy logic, evolutionary computation, pattern recognition, hybrid intelligent systems, symbolic machine learning, statistical models, image/audio/video compression and retrieval.